The task of manually controlling the robot combined with various operator straining factors, increase the cognitive workload of the operator [1]}. Moving towards robotic systems that can actively assist the operators and reduce their workload can lead in reduced errors and improved performance [1]}, [3]}. The advantage of such HRS lies in the complementing capabilities of humans and Artificial Intelligence (AI). In a VA system control can be traded between a human operator and a robot by switching between different Levels of Autonomy [4]}, e.g. the robot can navigate autonomously while the operator is multitasking. Levels of Autonomy (LOAs) refer to the degree to which the robot, or any artificial agent, takes its own decisions and acts autonomously [5]}. This work addresses the problem of dynamically changing LOA during task execution using a form of VA called Mixed-Initiative control. Mixed-initiative (MI) refers to a VA system where both the human operator and the robot's AI have authority to initiate actions and to change the LOA [6]}.
